Assessing the significance of tourism and climate on residential water demand: Panel-data analysis and non-linear modelling of monthly water consumptions. (May 2018)

• Record Type: Journal Article
• Authors: Toth, Elena; Bragalli, Cristiana; Neri, Mattia
• Is Part Of: Environmental modelling & software. Volume 103(2018)
• Page Start: 52
• Page End: 61
• Publication Date: 2018-05
• Subjects: Water demand modelling -- Residential water uses -- Tourism -- Climate -- Correlation analysis -- Panel-data; Environmental monitoring -- Computer programs -- Periodicals; Ecology -- Computer simulation -- Periodicals; Digital computer simulation -- Periodicals; Computer software -- Periodicals; Environmental Monitoring -- Periodicals; Computer Simulation -- Periodicals; Environnement -- Surveillance -- Logiciels -- Périodiques; Écologie -- Simulation, Méthodes de -- Périodiques; Simulation par ordinateur -- Périodiques; Logiciels -- Périodiques; Computer software; Digital computer simulation; Ecology -- Computer simulation; Environmental monitoring -- Computer programs; Periodicals; Electronic journals; 363.70015118
• DOI: 10.1016/j.envsoft.2018.01.011
• Languages: English
• ISSNs: 1364-8152

Abstract

Abstract: The concentration in time and space of tourists and of specific water-demanding touristic activities can add considerable pressure on available water supplies in coastal regions. The impact of tourism has not been adequately addressed in the water demand literature, especially at sub-annual scale: the present study includes the role of tourism on the monthly water demand in a set of Mediterranean coastal municipalities in a panel data framework. The influence of both climatic and touristic drivers on the water demand is investigated through a correlation analysis, thus deconstructing the seasonal variability of the consumption, and the development of both linear and non-linear models. The results demonstrate the improvement allowed by non-linear over linear modelling and the value of the information embedded in both climatic (in particular temperature daily maxima and minima and number of rainy days) and touristic determinants as drivers for the water demand at sub-annual scale. Highlights: Tourism industry may substantially influence the water demand in many cities. Need to consider the impact of both climate and tourism on subannual water demand. Novelty: use of data on tourists' presence as drivers for water demand models. Panel-data modelling (monthly demand for a set of seaside touristic cities). Input saliency analysis and linear and non-linear models are implemented.